At theScore, we are always looking for intelligent, resourceful, full-stack developers to join our growing team. To help us evaluate new talent, we have created this take-home interview question. This question should take you no more than a few hours.

All candidates must complete this before the possibility of an in-person interview. During the in-person interview, your submitted project will be used as the base for further extensions.

In-person coding interviews can be stressful and can hide some people's full potential. A take-home gives you a chance work in a less stressful environment and showcase your talent.

We want you to be at your best and most comfortable.

As outlined in our job description, you will come across technologies which include a server-side web framework (like Elixir/Phoenix, Ruby on Rails or a modern Javascript framework) and a front-end Javascript framework (like ReactJS)

We have sets of records representing football players' rushing statistics. All records have the following attributes:

• Player (Player's name)
• Team (Player's team abbreviation)
• Pos (Player's postion)
• Att/G (Rushing Attempts Per Game Average)
• Att (Rushing Attempts)
• Yds (Total Rushing Yards)
• Avg (Rushing Average Yards Per Attempt)
• Yds/G (Rushing Yards Per Game)
• TD (Total Rushing Touchdowns)
• Lng (Longest Rush -- a T represents a touchdown occurred)
• 1st (Rushing First Downs)
• 1st% (Rushing First Down Percentage)
• 20+ (Rushing 20+ Yards Each)
• 40+ (Rushing 40+ Yards Each)
• FUM (Rushing Fumbles)

In this repo is a sample data file rushing.json.

1. Create a web app. This must be able to do the following steps

   1. Create a webpage which displays a table with the contents of rushing.json
   2. The user should be able to sort the players by Total Rushing Yards, Longest Rush and Total Rushing Touchdowns
   3. The user should be able to filter by the player's name
   4. The user should be able to download the sorted data as a CSV, as well as a filtered subset

2. The system should be able to potentially support larger sets of data on the order of 10k records.

3. Update the section Installation and running this solution in the README file explaining how to run your code

1. Download this repo
2. Complete the problem outlined in the Requirements section
3. In your personal public GitHub repo, create a new public repo with this implementation
4. Provide this link to your contact at theScore

We will evaluate you on your ability to solve the problem defined in the requirements section as well as your choice of frameworks, and general coding style.

If you have any questions regarding requirements, do not hesitate to email your contact at theScore for clarification.

Before Installation, ensure you have node.js and mongo db installed on your device.

• Clone the Repository

git clone [email protected]:fidelisojeah/nfl-rushing.git

• Install Dependencies

npm install

• Install Frontend Dependencies

cd client
npm install

• Configure Environment Variables

  • Configure Environment Variables as specified Here

The applications tests are run with jest

npm run test

The backend of the application uses nodemon to enable quick reload on changes

npm run start:dev

The frontend of the application is bootstraped with create react app. Running it involves

• Starting up the backend

• Moving into the client folder

cd client

• Starting up the client application

npm run start

If you had set the PORT env variable for the backend, ensure you set the REACT_APP_SERVER to point to the backend

it is possible to run the application with docker.

Simply have docker installed on your machine.

docker-compose up

...

The following Environment variables need to be set and exported for application to function properly

MONGO_URI= The database credentials
LOGGER_LEVEL=debug